Sparse nonnegative matrix factorization with the elastic net

Authors

Weixiang Liu
Songfeng Zheng, Missouri State UniversityFollow
Sen Jia
Linlin Shen
Xianghua Fu

Abstract

Nonnegative matrix factorization is used extensively for feature extraction and clustering analysis. Recently many sparsity/sparseness constraints, such as L1 penalty, are introduced for sparse nonnegative matrix factorization. Inspired by sparsity measures from linear regression model, this paper proposes to integrate nonnegative matrix factorization with another sparsity constraint, the elastic net. The experimental results of clustering analysis on three gene expression datasets demonstrate the effectiveness of the proposed method.

Department(s)

Mathematics

Document Type

Conference Proceeding

DOI

https://doi.org/10.1109/BIBM.2010.5706574

Keywords

Clustering analysis, Gene expression data, Nonnegative matrix factorization, Sparsity penalty

Publication Date

12-1-2010

Recommended Citation

Liu, Weixiang, Songfeng Zheng, Sen Jia, Linlin Shen, and Xianghua Fu. "Sparse nonnegative matrix factorization with the elastic net." In 2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 265-268. IEEE, 2010.

Journal Title

Proceedings - 2010 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2010